Triple

T12039763
Position Surface form Disambiguated ID Type / Status
Subject Yoruboid languages E286629 entity
Predicate hasMember P10 FINISHED
Object Owe language
Owe language is a Yoruboid language spoken primarily in parts of Nigeria, closely related to Yoruba and sharing many of its linguistic features.
 E961851 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Owe language | Statement: [Yoruboid languages, hasMember, Owe language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Owe language
Context triple: [Yoruboid languages, hasMember, Owe language]
  • A. Wa language
    The Wa language is a Mon–Khmer language spoken primarily by the Wa people in parts of Myanmar and China.
  • B. Ao language
    Ao language is a Sino-Tibetan language spoken primarily by the Ao Naga people in Nagaland, India.
  • C. Wewewa language
    The Wewewa language is an Austronesian language spoken by the Wewewa people on the western part of Sumba Island in eastern Indonesia.
  • D. Warekena language
    The Warekena language is an indigenous Arawakan language spoken by the Warekena people of the Rio Negro region in Brazil and Venezuela.
  • E. Towa language
    Towa is a Native American language spoken by the Towa (Jemez) people of New Mexico and is part of the Puebloan language family.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Owe language
Triple: [Yoruboid languages, hasMember, Owe language]
Generated description
Owe language is a Yoruboid language spoken primarily in parts of Nigeria, closely related to Yoruba and sharing many of its linguistic features.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Owe language
Target entity description: Owe language is a Yoruboid language spoken primarily in parts of Nigeria, closely related to Yoruba and sharing many of its linguistic features.
  • A. Wa language
    The Wa language is a Mon–Khmer language spoken primarily by the Wa people in parts of Myanmar and China.
  • B. Ao language
    Ao language is a Sino-Tibetan language spoken primarily by the Ao Naga people in Nagaland, India.
  • C. Wewewa language
    The Wewewa language is an Austronesian language spoken by the Wewewa people on the western part of Sumba Island in eastern Indonesia.
  • D. Warekena language
    The Warekena language is an indigenous Arawakan language spoken by the Warekena people of the Rio Negro region in Brazil and Venezuela.
  • E. Towa language
    Towa is a Native American language spoken by the Towa (Jemez) people of New Mexico and is part of the Puebloan language family.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040c1a6c8190aea1388e82dd8f5a completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d9937a08190b2f606a1e55733b5 completed May 1, 2026, 12:33 p.m.
NEDg Description generation batch_69f53d9460bc8190869f2b7d095d98cb completed May 1, 2026, 11:56 p.m.
NED2 Entity disambiguation (via description) batch_69f564d2b4348190abf2d09ae00aea37 completed May 2, 2026, 2:43 a.m.
Created at: April 8, 2026, 9:47 p.m.